University of Louisiana at Lafayette

Other

Arun Lakhotia

Andrew Eric Walenstein

Md Enamul Karim

Herein disclosed is a method for automatically extracting signatures for malware. The method takes advantage of a fundamental economic requirement of malware authors: they must reuse code to manage the time investment. The method disclosed finds shared code between malware and generates signatures from the code. A method is also disclosed for separating code that is found predominantly, if not exceptionally, in malware from code that may be found in benign program.

Method for automatic creation of malware detection signature

Certain embodiments of the present invention are configured to facilitate analyzing computer code more efficiently. For example, by conducting a first level abstraction (e.g., symbolic interpretation and algebraic simplification) and a second level abstraction (e.g., generalization) of the computer code, the analysis may more accurately account for variations in the code that may occur as a result of register renaming, instruction reordering, choice of instructions, etc. while minimizing the cost of computations required to perform the analysis.

System and method for identifying and comparing code by semantic abstractions

A method is provided for comparing malware or other types of computer programs, and for optionally using such a comparison method for (a) searching for matching programs in a collection of programs, (b) classifying programs, and (c) constructing a classification or a partitioning within a collection of programs. In general, there are three steps to the comparison portion: selecting and extracting tokens from a pair of programs for comparison, building features from these tokens, and comparing the programs based on the frequency of feature occurrences to produce a similarity measure. Pairwise similarity is then used for optionally searching, classifying, or constructing classification systems.

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Lafayette, LA, United States of America

Arun Lakhotia